Technical Field
The techniques described herein relate generally to image processing. Some embodiments relate to processing imaging data contaminated by sensor-dependent noise.
Discussion of the Related Art
Complementary metal-oxide semiconductor (CMOS) cameras convert optical signals (e.g., visible light) into electrical signals, which can be processed to form images or to determine attributes of an imaged region. CMOS cameras typically include an array of pixel sensors (“pixels”), each of which includes a photosensitive region for converting optical signals to electrical signals, and a readout structure for amplifying the converted electrical signals and/or supplying the converted electrical signals to data processing components.
CMOS cameras can introduce some noise into the electrical signals corresponding to an imaged region. One type of noise introduced by CMOS cameras is “readout noise.” Readout noise, which refers to noise introduced by a camera's readout circuitry (e.g., the amplification circuitry, the analog-to-digital conversion circuitry, and the circuitry that couples a pixel's signal to data processing components), may also be modeled as a random variable with a Gaussian probability distribution. Readout noise is said to be “pixel-dependent” because the characteristics of a CMOS camera's readout noise may vary from pixel to pixel.
Another type of noise introduced by CMOS cameras is “photon shot noise” or “shot noise.” Shot noise, which arises from the photon detection process and may be significant when the number of photons incident on a pixel's photosensitive region is small (e.g., under low-light conditions), may be modeled as a random variable with a Poisson distribution. Shot noise depends on the number of incident photons and is therefore correlated with the input signal.
Some quantitative imaging techniques, such as single-molecule localization techniques (e.g., localization-based nanoscopy and/or single-particle tracking), rely on accurate and precise localization of single molecules. As just one example, single-molecule switching nanoscopy (SMSN) techniques are used to localize single molecules (e.g., with precisions on the order of approximately 10 nm) by stochastically switching single molecules on and off. A plurality of camera frames (e.g., hundreds, thousands, or even tens of thousands of camera frames) of blinking subsets of molecules may be recorded to obtain a single image with a resolution of approximately 25 nm to 40 nm. The temporal and spatial resolutions of such images are limited by several factors, including the number of photons emitted by a single molecule per frame, the sensitivity (e.g., quantum efficiency) of the camera, and the readout speed of the camera.